Our objective is to develop and test better methods of quantitatively evaluating the pathology of prostate cancer so as to enhance detection and prediction of prognosis. Utilizing various image analysis systems in conjunction with routine histologic parameters, we will analyze 1000 totally embedded radical prostatectomy specimens. Our specific aims are: 1) Prospective evaluation of combination of chromatin texture analysis, nuclear morphometry, and DNA ploidy as predictors of disease recurrence following radical prostatectomy in a group of 420 men with stage T2b and stage T2c prostate cancer; 2) Investigation of previously untested biomarkers for prostate cancers to predict progression following radical prostatectomy. These include: 1) cell death and proliferation markers; 2) neuroendocrine markers; 3) angiogenesis markers; 4) fatty acid synthase (OA519); 5) BCL-2; 6) E-cadherin; and 7) fluorescent in situ hybridization (FISH) for chromosomes 8, 8p, and 8q; 3) Investigation of the use of chromatin texture, nuclear morphometry and other various biomarkers to provide prognostic information on biopsy material; 4) Prospective validation of study published in JAMA to predict "insignificant" vs. "significant" disease based on needle biopsy findings and serum PSA measurements in men with non-palpable prostrate cancer; 5) Pathological evaluation of cases of hereditary prostate cancer utilizing DNA ploidy, chromatin texture, serum and tissue biomarkers, and nuclear morphometry; 6) Clinical and pathological studies evaluating the newly described monoclonal antibodies to bound and free forms of PSA, 7) Development of a computer assisted architectural grading system based on objective reproducible quantitative tumor characteristics. The above studies will aim to distinguish relatively indolent prostate cancers which could possibly be managed conservatively from those more aggressive tumors requiring therapy. This issue is increasingly important, with the enhanced detection by screening techniques of earlier prostate cancers of uncertain biologic malignancy. A prediction of patients with a higher probability for tumor progression will also be required for administering of adjuvant therapy.